Abstract
Driven by the continuous growth of maritime activities such as shipping, resource development, and rescue operations, the demand for highly reliable maritime communication is steadily increasing. This paper proposes a maritime end-to-end autoencoder communication system based on compressed channel feedback (CF-Dense-MAE), building on the existing maritime autoencoder communication system, aimed at enhancing the reliability of data transmission in maritime environments. CF-Dense-MAE integrates feedback encoder and decoder to learn richer signal features through channel feedback and quadratic coding. To reduce feedback overhead, we design an efficient compressed channel feedback mechanism by adjusting the output dimension of the feedback encoder and reconstructing the data in the feedback decoder. CF-Dense-MAE has been trained in environments with Rician fading channels and additive white Gaussian noise, and its model parameters are optimized with a large amount of data. Simulation results show that CF-Dense-MAE outperforms the baseline in terms of block error rate performance, validating its stronger generalization capabilities and communication reliability. With lower feedback overhead, CF-Dense-MAE can provide stable and highly reliable communication services, adapting to complex maritime environments.
The work was supported by the National Natural Science Foundation of China (No. 51939001, No. 62371085) and Fundamental Research Funds for the Central Universities (No. 3132023514).
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Han, X., Lin, B., Shao, S., Wu, N. (2025). Design of Maritime End-to-End Autoencoder Communication System Based on Compressed Channel Feedback. In: Cai, Z., Takabi, D., Guo, S., Zou, Y. (eds) Wireless Artificial Intelligent Computing Systems and Applications. WASA 2024. Lecture Notes in Computer Science, vol 14997. Springer, Cham. https://doi.org/10.1007/978-3-031-71464-1_9
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